Your Best AI Strategy Starts at the Top

We are hosting a day-long Claude Code for Absolute Beginners course on April 14. If you have used Claude Code for an hour or less, or not at all, I’ll get you set up, help you build your first app with Claude Code, and start automating your routine tasks.—Mike Taylor

A CEO told us recently that he’d been hoping to skip the part where AI wasn’t very good. He figured he’d jump in once the technology matured past the clunky, overpromising phase because carving out hours to learn a new category of technology felt untenable with all of his other responsibilities.

That wait-and-see posture made sense for a while. It doesn’t anymore. When Anthropic released industry-specific plugins for its Cowork tool in February 2026 for legal and financial services roles, the S&P 500 software index fell nearly nine percent over a few days. Executives who haven’t touched the tools themselves are now making high-stakes decisions about something they don’t understand firsthand.

The problem is what they default to. When a leadership team hasn’t used AI themselves, they treat it like any other software purchase: Evaluate, buy, and plug in. They ask, “Which platform?” and “How does it integrate?” Those are the right questions for most technology. They’re the wrong questions for AI.

AI tools like Claude and Cowork aren’t products that slot into your tech stack and deliver value on day one. They’re more like a new kind of employee—one that can do enormous amounts of work, but only if you tell it exactly what to do and check whether the output is right. That’s a fundamentally different adoption decision, and one that’s hard to make unless they have experienced the tool’s capabilities firsthand.

More executives seem to be waking up to this, as we’ve recently started receiving inbound requests from executives at companies like Thumbtack and Headway (Every consulting clients) to attend their executive offsites and walk them through using Claude Code to build real projects. Our conversations with executives had always been about training their teams, and the rapid progress in AI has made them want to get in on the action, too. We’re finding skills they’ve already built as leaders are the skills AI demands—it’s just a case of getting into the habit of applying them.

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Executives realize AI is like managing people

Firsthand experience matters so much because AI, when you actually use it, doesn’t feel like software. It feels like managing people. This is what we’ve found surprises the executives we’ve worked with the most—the fact that the work feels familiar.

Think about what it takes to manage people well. You need to know what the goal is, break work into pieces, assign those pieces to the right people, and check the output without micromanaging. You need the judgment to notice when something looks right on the surface but doesn’t hold up—the kind of pattern recognition that comes from years of making mistakes and learning from them.

Managing AI is the same work. When you use a tool like Claude Cowork, you’re running 10 threads at once—building dashboards, summarizing your inbox, and reviewing documents—each tackling a different task. Your job is to delegate clearly, check the output, and apply the judgment that the AI doesn’t have. Did it pull the right data? Does this analysis match what I know about the market? Is the logic sound, or did it take a shortcut that looks plausible but isn’t?

This is why the “evaluate and buy” approach to AI tools fails. You can’t evaluate an employee by...

1. What AI means for the kind of people executives should be hiring right now
2. What a chief people officer built in a single session that replaced three hours of manual work weekly
3. The reason senior executives have a hidden advantage over junior employees when it comes to getting value from AI tools